Methods for assessing and optimizing muscular performance

ABSTRACT

A muscle assessment protocol can include: attaching one or more surface electromyometry (sEMG) sensors to the skin of a subject to be operably coupled with one or more muscles; operably coupling the one or more sEMG sensors to a computing system; performing the predetermined muscle activity of a muscle assessment protocol that includes one or more of a muscleprint protocol, stride rate tuning protocol, controlled activity training protocol, or frequency-based, or amplitude-adjusted root mean square protocol; monitoring/recording sEMG data of the one or more muscles during the predetermined muscle activity; and providing the sEMG data to the subject such that the subject can improve muscle performance for the predetermined muscle activity by using the sEMG data. The muscle activity includes static or dynamic muscle use. The predetermined muscle activity can be provided to the subject by the computing system.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application claims the benefit of U.S. ProvisionalApplication Nos. 61/385,046, 61/385,038, 61/385,048, 61/385,049,61/385,051, and 61/385,053 all of which were filed on Sep. 21, 2010. Inaddition, this patent application claims the benefit of U.S. ProvisionalApplication No. 61/514,148, filed Aug. 2, 2011. All of theaforementioned provisional applications are incorporated herein byspecific reference in their entirety.

BACKGROUND

Generally, there are various methods for monitoring and analyzing musclecondition and/or performance. Often, such muscle monitoring and analysisinvolves some form of myometry, which measures the strength of a muscleby measuring the force that the muscle can generate. For an example ofmyometry, a user squeezes a device which in turn measures and transmitsforce information back to a computer, and the computer computes aforce/time curve. The measurement is usually via electronic components,and thereby can be referred to as electromyometry. These electronicdevices are typically fully wired systems that require immediateproximity to a computer, and which are designed to be operated byphysicians or clinicians in appropriate controlled settings.

Surface electromyometry (sEMG) is a type of myometry that uses surfacesensors to obtain information about the functionality of one or moremuscles during a muscular activity. The sEMG assessments can be sortedinto three general groups of muscle activity: static muscle activity,dynamic muscle activity, or combination of static and dynamic muscleactivities. The different muscle activity paradigms can be useful fordifferent muscle assessments.

A static muscle activity may occur with no load (i.e. sitting) or withan isometric load (no movement of limb). Static muscle activityevaluation can include observation of the rectified amplitude of thesEMG data. The static muscle activity evaluation can be useful for aspecific muscle or muscle group or as a comparison to other muscles ormuscle groups. Absolute levels of the sEMG data can be monitored throughroot mean square of the sEMG amplitude (e.g., RMS sEMG amplitude), andabnormally large values of the RMS sEMG can be identified or determined.Rhythmic contraction patterns of the muscle or muscle groups can beidentified or determined, and may also be based on rectified amplitude.During an isometric loading protocol, a user can exert an amount offorce while keeping the limb fixed in a single position. Usually, theforce exerted is measured as a fixed percentage of Maximum VoluntaryContraction (MVC). Then, the median frequency (MF) or mean powerfrequency (MPF) can be measured or determined by observing or analyzingthe frequency spectrum of the sEMG. In this manner, the fatigue level ofthe muscles can be established, and the point at which fatigue begins tooccur may be identified.

Dynamic muscle activity evaluations can ascertain relationships betweensEMG amplitude and force, which have been shown to be “curvilinear”, ornon-linear at the extremes of the force range (e.g., very little force,or a lot of force) and essentially linear for the majority of theforce/amplitude relationship. Evaluating that relationship is useful fordynamic muscle activity sEMG evaluation. Methods for implementingdynamic muscle activity evaluations can include incrementally increasingthe force exerted by the muscle by way of a machine that measures force,and measuring the sEMG amplitude of the muscle activity that isassociated with various force levels. Dynamic muscle activityevaluations can be used in the evaluation of torque and paralysis. Thereare dynamic muscle activity evaluation methods for: muscle imbalance,trigger points, cocontractions, and fasciculations.

However, the abovementioned muscle assessment methods can be used toassess a variety of pathologies and physiological states which maycorrespond to (or attempt to correspond to) clinical and/or medicalconditions. These methods have typically been designed to be performedby specialists (e.g., MD, chiropractor, physical therapist, etc.).However, these muscle assessment methods are usually restricted tocontrolled settings in the presence of these specialists. Thus, there isnot a way for a common person to implement muscular assessment on theirown. Therefore, there remains a need to bring the ability to implementmuscle assessment to the masses.

BRIEF DESCRIPTION OF THE FIGURES

The foregoing and following information as well as other features ofthis disclosure will become more fully apparent from the followingdescription and appended claims, taken in conjunction with theaccompanying drawings. Understanding that these drawings depict onlyseveral embodiments in accordance with the disclosure and are,therefore, not to be considered limiting of its scope, the disclosurewill be described with additional specificity and detail through use ofthe accompanying drawings, in which:

FIG. 1A includes a graph that illustrates speed versus time of a subjectduring a muscleprint exercise routine that is conducted as a “step-uptest,” where the exercise can be walking, jogging, running, cycling, orthe like;

FIG. 1B includes a graph that illustrates surface electromyography(sEMG) amplitude versus time with a decay period later in time of aSubject during a muscleprint exercise routine that is conducted as a“step-up test;”

FIG. 1C includes a graph that illustrates frequency-based,amplitude-adjusted RMS sEMG versus time with a decay period (e.g., RMSof decay in dashed box) later in time of a subject during a muscleprintexercise routine that is conducted as a “step-up test;”

FIG. 1D includes a graph that illustrates sEMG amplitude (e.g., microV)versus time (e.g., minutes) of a subject during a muscleprint exerciseroutine that is conducted as a “step-up test,” with speed constant withrespect to time;

FIG. 2A includes a graph that illustrates sEMG amplitude versus time(e.g., arbitrary unit) of a subject during a muscleprint exerciseroutine that is conducted as a “step-up test,” where Period (1)indicates a “transition” (e.g., from standing to full squat), Period (2)indicates being “stationary” (e.g., staying in squat before a jump),Period (3) indicates a “transition” (e.g., jumping up), Period (4)indicates a “transition” (e.g., absorbing impact or weight or force oflanding from jump), Period (5) indicates being “stationary” (e.g.,staying in squat before rising), and Period (6) indicates a “transition”(e.g., rise to standing);

FIG. 2B includes a graph that illustrates weight versus time per rep(i.e., time/rep) of a subject during a muscleprint weightliftingexercise routine that is conducted as a weightlifting “step-up test,”where each horizontal line represents a 5 pound increment increase, andwhile the weightlifting exercise routine can be a machine bench press,any weight lifting exercise can be conducted ant the weight incrementincrease can vary;

FIG. 2C includes a graph that illustrates sEMG amplitude versus time perrep (i.e., time/rep) of a subject during a muscleprint weightliftingexercise routine that is conducted as a weightlifting “step-up test,”

FIG. 3A includes a graph that illustrates sEMG amplitude versus time ofa subject during a muscleprint exercise routine that has anaction-hold-release protocol, and is exemplified by a using a bow todraw-hold-release;

FIG. 3B includes a graph that illustrates sEMG amplitude versus time oftwo different subjects during a muscleprint exercise routine that has anaction-hold-release protocol, and is exemplified by a using a bow todraw-hold-release;

FIG. 3C includes a graph that illustrates sEMG amplitude versus time ofa subject compared to a database of subjects (e.g., similar subjects insize, weight, height age, condition, etc.) during a muscleprint exerciseroutine that has an action-hold-release protocol, and is exemplified bya using a bow to draw-hold-release;

FIG. 3D includes a graph that illustrates sEMG amplitude versus time ofa subject compared to an entire database of subjects during amuscleprint exercise routine that has an action-hold-release protocol,and is exemplified by a using a bow to draw-hold-release;

FIG. 4A includes a graph that illustrates sEMG amplitude versus time,where the sEMG amplitude is a metric observed during a muscleprintexercise routine such as walking, jogging, running, cycling, or thelike;

FIG. 4B includes a graph that illustrates sEMG amplitude versus time,where the sEMG amplitude is an average rectified amplitude during amuscleprint exercise routine such as walking, jogging, running, cycling,or the like;

FIG. 4C includes a graph that illustrates sEMG amplitude versus time,where the sEMG amplitude is an integrated sEMG or area under curve ofFIG. 4A during a muscleprint exercise routine such as walking, jogging,running, cycling, or the like;

FIG. 4D includes a graph that illustrates mean power frequency (i.e.,MPF) versus time, where the MPF may be a mean power frequency varianceobserved during a muscleprint exercise routine such as walking, jogging,running, cycling, or the like;

FIG. 4E includes a graph that illustrates mean power frequency (i.e.,MPF) versus time, where the MPF may be a mean power frequency varianceobserved during a muscleprint exercise routine such as “step-up test”routine or weightlifting routine or the like;

FIG. 4F includes a graph that illustrates RMS sEMG versus time orfrequency-based, amplitude-adjusted RMS sEMG versus time (i.e., FBAAR v.time) during a muscleprint exercise routine such as walking, jogging,running, cycling, or the like;

FIG. 5A includes a schematic representation of an exercise routine thatis measured at stride length versus speed versus stride rate, whereinthe stride length is measured as distance between right footheal-strikes of a single stride;

FIG. 5B includes a schematic representation of an exercise routine thatis measured at half strides or for each heal strike of both feet;

FIG. 6A includes a graph that illustrates stride rate versus time, wherespeed is constant throughout exercise routine at 5.5 MPH, where striderate is held constant up to 20 minutes and then initially decreasedbefore being increased in a “step-up test;”

FIG. 6B includes a graph that illustrates cumulative integral versustime for FIG. 6A, where speed is constant throughout exercise routine at5.5 MPH in a “warm-up period;”

FIG. 7A includes a graph that illustrates sEMG amplitude versus time orspeed versus time, where speed is constant throughout exercise routine;

FIG. 7B includes a graph that illustrates sEMG amplitude versus time orspeed versus time, where speed is controlled to keep sEMG amplitudeunder a limit throughout exercise routine, and exhaustion is delayed;

FIG. 8A includes a graph that illustrates sEMG amplitude versus time fora set time of consistent exercise (e.g., running etc.) followed by restor non-exercise, where an inflection point is identified;

FIG. 8B includes a graph that illustrates sEMG amplitude versus time fora set time of consistent exercise (e.g., weight lifting or otherperiodic exercise) followed by rest or non-exercise, which is shown asexercise-rest-exercise-rest-exercise;

FIG. 8C includes a graph that illustrates sEMG amplitude versus time fora set time of consistent exercise (e.g., weight lifting or otherperiodic exercise) followed by rest or non-exercise, which is shown asexercise-rest-exercise-rest-exercise, where FIG. 8C is an alternativeprofile compared to FIG. 8B;

FIG. 9A includes a graph that illustrates sEMG amplitude versus time orMPF versus time of a subject during an exercise routine that isconducted as a constant rate, such as 5.5 MPH with a 135 BPM striderate, where data can be from left quad;

FIG. 9B includes a graph that illustrates frequency-based,amplitude-adjusted RMS sEMG versus time (i.e., FBAAR v. time) of asubject during an exercise routine that is conducted as a constant rate,such as 5.5 MPH with a 135 RPM stride rate, where data can be from leftquad;

FIG. 10A includes a graph similar to FIG. 8A;

FIG. 10B includes a graph that illustrates sEMG amplitude versusfrequency-for a non-fatigued muscle spectrum from FIG. 10A, and showsthe MPF;

FIG. 10C includes a graph that illustrates sEMG amplitude versusfrequency for a fatigued muscle spectrum from FIG. 10A, and shows theMPF;

FIG. 11 includes a schematic representation of a computing system thatcan be used in the systems and methods of the present invention; and

FIGS. 12-15 include flow diagrams for different methods, which can beperformed as described herein, where one or more steps may be omitted,arranged in accordance with at least one of the embodiments describedherein, and which arrangement may be modified in accordance with thedisclosure provided herein by one of ordinary skill in the art. Theimages in the graphs may or may not be to scale.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.

Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented herein. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein.

Generally, the present invention includes systems and methods forimplementing muscle assessment protocols. The assessment protocols canbe implemented in a manner such that a common person can obtain accuratemuscle information. The inventive muscle assessment protocols can beimplemented with the aide of computing systems and software with userinterfaces to facilitate use by a common person. The muscle assessmentprotocols can be implemented without controlled settings or specialists.As such, the muscle assessment protocols described herein may be usefulfor monitoring and analyzing muscle function of healthy individuals, andtherefore may not be used in connection with determination or monitoringof disease states. The muscle assessment protocols can be used forpersonal use, which may include analysis of an exercise routine as wellas the musculature benefits, improvements, or declines that may occur.The muscle assessment protocols can be used to monitor and analyzemuscular performance of an athletic subject who already is relativelyhealthy, but who may desire improvement in their overall health orathletic performance, or general muscle maintenance.

The muscle assessment protocols can be designed and implemented for theassessment of muscular performance for athletic consumers. Theseprotocols differ from standard medical and clinical assessmenttechniques in a variety of ways. One example of a differentiating factoris that the inventive muscle assessment protocols are designed forimplementation that is automatic and software-driven. Ease of use allowsany subject to receive the benefit of muscle assessment. Anotherdistinguishing factor includes the inventive muscle assessment protocolsbeing designed and implemented as standard actions for a wide variety ofdifferent muscle activities for one or more muscles, exercisedisciplines, of for one or more specific muscles. Also, the muscleassessment protocols can be performed by a common person withoutspecific equipment other than one or more sensors that can be worn onthe subject as well as a computing system for measuring, recording, andanalyzing the data obtained during the protocol. This differs from thestrategy of an assessor having a number of different assessment tools attheir disposal, and relying upon judgment to determine which is best fora particular individual (typically, with the goal of diagnosis in mind).

The muscle assessment protocols can use computing systems and softwarefor measuring, recording, and analyzing the data from the subject havingtheir muscles being assessed. The protocols can focus on single muscleor muscle group performance assessment from the perspective of basicmuscle functional through muscle performance enhancement as well asoptimization of muscular performance. The protocols can be implementedwith one or more muscles for short and/or long periods of physicalexertion in static, dynamic and/or combined static and dynamic muscleactivities.

In one embodiment, the present invention provides a method forperforming a muscle assessment protocol. FIG. 12 illustrates anembodiment of a method for performing the muscle assessment protocol 1,which can include: attaching one or more surface electromyometry (sEMG)sensors to the skin of a subject so as to be operably coupled with oneor more muscles of the subject (Attach Sensor to Skin,” block 10);operably coupling the one or more sEMG sensors to a computing system(“Link Sensor to Computer,” block 12); performing the predeterminedmuscle activity of a muscle assessment protocol (“Perform PredeterminedMuscle Activity,” block 14) that includes one or more of a muscleprintprotocol, stride rate tuning protocol, controlled activity trainingprotocol, or frequency-based, or amplitude-adjusted root mean squareprotocol; monitoring and/or recording sEMG data of the one or moremuscles during the predetermined muscle activity (“Monitor/Record sEMGData,” block 16); and providing the sEMG data to the subject such thatthe subject can improve muscle performance for the predetermined muscleactivity by using the sEMG data (“Provide sEMG Data to Subject,” block18). The muscle activity includes static (e.g., resistance against aload) or dynamic muscle use. The predetermined muscle activity can beprovided to the subject by the computing system. The muscle activity caninclude a continuous exercise routine or a noncontinuous exerciseroutine. The continuous exercise routine can include one or more ofwalking, jogging, running, sprinting, hiking, cycling, rollerblading,roller skating, skiing, cross-country skiing, rowing, swimming,snowboarding, yoga, pilates, and the like. The noncontinuous exerciseroutine can include one or more of firing an arrow from a bow,weightlifting, golf swing, bat swing, ball throw, punch, kick, jumping,squatting, or the like.

The muscle assessment protocols can include a series of assessedactivities that provide data that can be analyzed in order to provide asubject with a better understanding of the muscular activity andresponse patterns. Once a muscle response pattern can be, determined,then strategies can be implemented so that optimal muscle performancecan be targeted and hopefully achieved. The muscle assessment protocolscan be described as: a muscleprint protocol; a stride rate tuningprotocol; a controlled activity training protocol, or a frequency-based,amplitude-adjusted root mean square protocol. A muscleprint is a muscleassessment protocol that monitors muscle sEMG data of a muscularresponse while a subject is engaged in an activity. In the muscleprintprotocol, the one or more sensors each monitor muscle sEMG data of theone or more muscles while the subject performs the predeterminedactivity in order to determine the subject's muscular capabilities ofthe one or more muscles over a defined period of time or portionthereof. Stride rate tuning is a muscle assessment protocol thatmonitors muscle sEMG data while a subject adjusts their caloricexpenditure during a controlled activity based on sEMG data measure andanalyzed, and then provided back to the subject during the protocol. Inthe stride rate tuning protocol, the one or more sensors monitor musclesEMG data while the subject adjusts their caloric consumption during acontrolled activity based on sEMG data that is measured and/or analyzed,and the sEMG data is provided to the subject in order to facilitate theadjustment of caloric consumption. Controlled activity training is amuscle assessment protocol where an sEMG metric or a derivative metricis kept constant during a particular physical activity and anon-quantitative, athletic activity is varied, which allows for precisetraining based on a quantitative metrics while engaged in inherentlysubjective activities. In the controlled activity training protocol, thesubject maintains substantially a constant sEMG metric or metricderivative or metric integral by varying muscle activity exertion duringthe predetermined muscle activity. Frequency-based, amplitude-adjustedroot mean square is a muscle assessment protocol that provides fordisplaying sEMG data that is adjusted to compensate for fatigue (e.g.,frequency-based) muscle signal dropout. In the frequency-based,amplitude-adjusted root mean square that includes displaying sEMG datathat is adjusted to compensate for muscle fatigue of the one or moremuscles.

The sEMG data can include a metric selected from: sEMG amplitude;instantaneous rectified sEMG amplitude; average rectified sEMGamplitude; area under sEMG curve; area over sEMG curve; integrated sEMG;derivative sEMG; frequency-based, amplitude adjusted RMS sEMG; meanpower frequency (MPF); muscle fatigue onset index (MFOI); or combinationthereof.

One implementation of the invention can be to compare different resultsof the same subject from a muscle activity performed at different times.Another implementation can be to compare different results of the samemuscle activity across multiple subjects. Traditionally, the subjectsare human, but the principle can be applied to non-human subjects, suchas dogs, horses, or the like. When comparing the data for a muscleactivity or the results of the muscle activity, the data can benormalized with respect to the muscle activity. The normalization can beon speed, repetitions, or other parameter of the muscle acidity. Withrunning as an example, the comparative relationships and amplitudelevels of the data can be linked to a particular speed. As such,normalization of the data can be performed before the comparison of thedata so that the data is relevant across the subjects. The normalizationcan adjust the levels to compare them as if they were recorded at thesame speed.

In one embodiment, muscle data can be used to create a referencedatabase. The database can include various types of muscle data, such asthe data described herein or the metrics of the data described in theincorporated references. For example, the database can include RMS EMGdata and frequency values for people of different age, sexes, shapes,size, BMI, and athletic condition. For example, the speed of a run canbe a parameter in the database. The database can include muscle data forall muscle optimization protocols described herein. The data can be rawdata or normalized data.

In one example, the database can be used to compare different subjects.The subjects can include a 25-year old man who is 6′5″ with 4% body fat,and a 80-year old woman who is 4′11″ with 18% body fat. It is likelythat these individuals do not perform muscle activities at the samelevel, and as such, the data or data values need to be normalized beforebeing compared. The computing system associated with the database canfacilitate adjustment of the recorded values between different subjectsin order to estimate what the values would be if they had the same age,sex, BMI, and activity speed.

The database can be used to provide data and information as well as toreceive data and information. The data can be used for direct ornormalized comparison between subjects. For example, the first time arun or test is performed by a subject and some kind of metric isproduced, comparisons and adjustments can be made to a referencedatabase of people with similar age, sex, BMI, and activity speed. Inanother example, if the user has never recorded a MVC or “pseudo-MVC”type of exercise, then these levels can be taken from a referencedatabase. Subsequent to initial tests, such as including MVC,pseudo-MVC, and any of the muscleprinting methods, the initial resultscan also be used in addition to the reference database values foradditional accuracy.

Muscleprint

Generally, the muscleprinting muscle assessment protocol can be designedto determine a subject's muscular capabilities during a muscle activityover a defined period of time in order to identify or determine a musclesEMG profile in response to the muscle activity. The defined period oftime can vary, and a portion or the whole time can be used. Much like afingerprint, a muscleprint is a unique snapshot of an individual'spersonal biometric characteristics for the given period of time. Unlikea fingerprint, a muscleprint may change for an individual over time asthe individual gets into better shape or as physiological changes occurfor the individual. Also unlike a fingerprint, a muscleprint cannot beused for identification purposes due to the ever changing muscleconditions and responses to the same or different activity. Whilemuscleprinting can be used for common athletic activities, it can alsobe used for any activity that uses a muscle that is static (e.g.,loaded) or dynamic.

Muscleprinting may be accomplished in a variety of ways. In one aspect,a muscleprinting protocol can be implemented with a “step-up test” for acontinuous or noncontinuous muscular activity. A particularly usefulcontinuous muscular activity for muscle printing is running because itcan result in the onset of fatigue before other similar activities,which results in a shorter assessment period of time. FIG. 1A includes agraph that illustrates speed versus time of a subject during amuscleprint exercise routine that is conducted as a “step-up test.” Fora running example, a treadmill can be used when programmed toincrementally increase the speed at defined time intervals. For example,the speed of the treadmill can be increased by 0.25 MPH for a definedperiod of time, such as 20 seconds. Examples of speed increases can be0.5 MPH, 1 MPH, 2 MPH, 3 MPH, 4 MPH, or higher for fit athletes. Forcontinuous muscular activities such as cycling where the rate is muchfaster, the speed increases can be multiplied by a factor, such as afactor of 5 or 10 depending on the fitness level of the subject. Thetime period can vary greatly, where the time period can be as short as20 to 30 seconds or as long as 10 minutes depending on the particularactivity. For example, running activities can have shorter periodsbetween step-up increases in speed, while cycling activities can havelonger periods between step-up increases. The protocol can also beimplemented with a subject that is capable of monitoring their speed andthen increasing their speed by increments after defined time periods. Inan actual experimental protocol, the step-up-test was structured asfollows: run at 1.0 MPH for a first period of 3 minutes; run at 1.5 MPHfor a second period of 3 minutes; run at 2.0 MPH for a third period oftime for 3 minutes; and so on at 0.5 MPH increments until 8.0 MPH or asfast as the subject can run in a sprint, or until fatigued. When step-upincrements result a final speed of 8.0 MPH, the total duration of thestep-up test can be 45 minutes.

FIG. 1B includes a graph that illustrates another example of surfaceelectromyography (sEMG) amplitude versus time study with a decay periodlater in time of a subject during a muscleprint exercise routine that isconducted as a “step-up test.” The metric observed and recorded for eachsection of the run was the average rectified sEMG amplitude. As shown inFIG. 1B, each step-up occurs, but the sEMG amplitude can vary betweeneach step. This can be a result of some fatigue or other reason why thesubject cannot maintain the identified speed. Accordingly, the graph inFIG. 1B can be obtained from the sEMG that was recorded from the speedstep-up of FIG. 1A.

FIG. 1C includes a graph that illustrates frequency-based,amplitude-adjusted RMS sEMG versus time with a decay period (e.g., RMSof decay in dashed box) later in time of a subject during a muscleprintexercise routine that is conducted as a “step-up test.” This graph canbe generated from the data of FIG. 1B.

There are a number of other types of muscleprinting algorithms which canbe implemented. A muscle printing algorithm can be determined to dependon the type of athletic activity. For instance, there is the “typicalrun” muscleprint for runners as shown in FIG. 1D. FIG. 1D includes agraph that illustrates sEMG amplitude (e.g., microV) versus time (e.g.,minutes) of a subject during a muscleprint exercise routine that isconducted as a “step-up test,” with speed constant with respect to time.One implementation of this method would require a runner to run for 30minutes at 5.0 MPH with a constant neutral stride rate, which results inthe change in sEMG amplitude over time. Also, the rate and duration canbe modulated depending on the subject.

In another example, a muscleprint protocol can include the activity of atransition muscle activity and then a stationary muscle activity, orvice versa. Also, the activity can include a first transition muscleactivity, a first stationary muscle activity, a second transition muscleactivity, and then a second stationary activity. The activity may alsobe a transition muscle activity, a stationary muscle activity, a secondtransition muscle activity, a third transition activity, and then asecond stationary activity. Accordingly, various combinations andarrangements of stationary and transition muscle activities can beimplemented. The transition activity can include squatting down, thestationary muscle activity can be staying squatted or otherwise waitingfor the next transition activity. Generally, the stationary muscleactivities do not involve movement or change in position, while thetransition muscle activities include active motion or movement orchanging position. One example can include holding a squat for astationary muscle activity and then jumping straight up into the air ashigh as possible with a stationary squat between each jump for a definednumber of times, such as 3 times, 5 times, 7 times, or 9 times in a rowor any number therebetween. These types of muscle activities can bedescribed as noncontinuous due to the way the muscle activity isimplemented not being continuous.

FIG. 2A includes a graph that illustrates sEMG amplitude versus time(e.g., arbitrary unit) of a subject during a muscleprint exerciseroutine that is conducted as a “step-up test,” where Period (1)indicates a “transition” (e.g., from standing to full squat), Period (2)indicates being “stationary” (e.g., staying in squat before a jump),Period (3) indicates a “transition” (e.g., jumping up), Period (4)indicates a “transition” (e.g., absorbing impact or weight or force oflanding from jump), Period (5) indicates being “stationary” (e.g.,staying in squat before rising), and Period (6) indicates a “transition”(e.g., rise to standing).

Additionally, step-up tests can be performed with noncontinuous athleticactivities. Examples of noncontinuous athletic activities includeweightlifting, throwing, kicking, punching, golfing, tennis, or othersthat have start-stop motions. Accordingly, weightlifting is a goodexample of a noncontinuous athletic activity can be performed during amuscleprint protocol. Weightlifting can be conducted with the step-uptest as well by using progressively heavier weights for a specificexercise such as biceps curls. For example, the weight can be increasedin increments of 5 pounds until exhaustion or a predefined weight limit,and certain measurements can be made, such as sEMG, at each weightincrement. The increase in rate or weight or resistance can be describedas an increase in muscle output or muscle effort. The sEMG data can beprocessed for rectified amplitude and/or mean power frequency (i.e.,MPF) during max amplitude of repetition of lifting the weight. This canallow for a muscleprint similar to the one developed for running, astep-up test described above for weightlifting or other noncontinuousmuscle activities.

FIG. 2B includes a graph that illustrates weight versus time per rep(i.e., time/rep) of a subject during a muscleprint weightliftingexercise routine that is conducted as a weightlifting “step-up test,”where each horizontal line represents a 5 pound increment increase, andwhile the weightlifting exercise routine can be a machine bench press,any weight lifting exercise can be conducted ant the weight incrementincrease can vary. FIG. 2C includes a graph that illustrates sEMGamplitude versus time per rep (i.e., time/rep) of a subject during amuscleprint weightlifting exercise routine that is conducted as aweightlifting “step-up test.”

The muscleprinting protocol can be implemented by processing datathrough the proper algorithm. As such, the subject of the muscleprintingprotocol can wear a device that records sEMG data, and the device can beconfigured to record sEMG output during all phases of muscleprintingactivities. This allows for the muscleprinting protocol to bothfacilitate a specific exercise plan, recordation of sEMG data during theexercise plan, and process the data to provide a subjective analysis ofthe subject's muscleprint. The muscleprint can then be used for analysisand strategizing exercise routines to improve muscle condition andfunction.

In one embodiment, the muscleprinting protocol can be used to recordquantitative biometric data (e.g., sEMG) in a standardized method toallow for comparisons to be made across time for a single individual,between different individuals, between an individual and a database ofmetrics taken for a subset of a large population, or compared to theentire database. The data obtained during a muscleprinting protocol canthen be input into a computing method for an automatic software-drivenassessment of an individual's muscular capabilities and a comparativeanalysis can be performed between the individual's data and the data ofone or more other individuals. These comparisons can result in data thatcan be provided to the individual in a manner that allows for visualcomparison of the performance data. The data can be illustrated for theindividual in a table, graph, or other visual display. Also, the datamay be converted to audio and played so that the individual can listento the results. The comparisons can be implemented for any type ofcontinuous or noncontinuous athletic activity, as well as other athleticactivities that use muscles. An example of an athletic activity that issuitable for such muscle printing comparative analysis can include thefiring of an arrow from a bow, which includes a draw-hold, releasemuscle performance profile, which can be considered a noncontinuousmuscle activity. FIGS. 3A-3D show the graphical output of for anindividual and then the comparison of the individual with one or moreother individuals.

FIG. 3A includes a graph that illustrates sEMG amplitude versus time ofa subject during a muscleprint exercise routine that has anaction-hold-release protocol, and is exemplified by a using a bow todraw-hold-release. This type of graph can be generated for substantiallyany muscle activity. While the X-axis identifies time at 10 seconds, thetime can vary for any stage of the muscle activity. Also, the durationcan be varied depending on the type of muscle activity.

FIG. 3B includes a graph that illustrates sEMG amplitude versus time oftwo different subjects during a muscleprint exercise routine that has anaction-hold-release protocol, and is exemplified by a using a bow todraw-hold-release. Such a comparison can be done between individualsthat know each other or random individuals. The second individual datacan be obtained from a database or from a known other user.

FIG. 3C includes a graph that illustrates sEMG amplitude versus time ofa subject compared to a database of subjects (e.g., similar subjects insize, weight, height age, condition, etc.) during a muscleprint exerciseroutine that has an action-hold-release protocol, and is exemplified bya using a bow to draw-hold-release. The database can be assessed over anetwork so that the individual can obtain the necessary information forthe comparative analysis. The individual user can then select forsimilar users using a variety of criteria.

FIG. 3D includes a graph that illustrates sEMG amplitude versus time ofa subject compared to an entire database of subjects during amuscleprint exercise routine that has an action-hold-release protocol,and is exemplified by a using a bow to draw-hold-release. The databasecan be continually updated by users providing their information to thedatabase. The database can then be accessed by qualified users, such asthe individual.

During the muscleprint, various types of data can be measured, recorded,and/or generated. The data can be relevant to various metrics that areuseful for assessment of the muscle activity, or change in muscleactivity'. Some examples of the metrics that can be recorded orgenerated during the muscleprint protocol include the following:instantaneous rectified sEMG amplitude (see FIG. 4A); average rectifiedsEMG amplitude (see FIG. 4B); area under the sEMG graph/integrated sEMG(FIG. 4C); mean power frequency (MPF) (see FIG. 4D). While all of FIGS.4A-4D illustrate metrics for a running muscle activity, FIG. 4E shows aweightlifting metric for MPF, which is visually different from forrunning. As such, the type of muscle activity can dictate the visualinformation of the graphical output. FIG. 4A includes a graph thatillustrates sEMG amplitude versus time, where the sEMG amplitude is ametric observed during a muscleprint exercise routine such as walking,jogging, running, cycling, or the like. FIG. 4B includes a graph thatillustrates sEMG amplitude versus time, where the sEMG amplitude is anaverage rectified amplitude during a muscleprint exercise routine suchas walking, jogging, running, cycling, or the like. FIG. 4C includes agraph that illustrates sEMG amplitude versus time, where the sEMGamplitude is an integrated sEMG or area under curve of FIG. 4A during amuscleprint exercise routine such as walking, jogging, running, cycling,or the like. FIG. 4D includes a graph that illustrates mean powerfrequency (i.e., MPF) versus time, where the MPF may be a mean powerfrequency variance observed during a muscleprint exercise routine suchas walking, jogging, running, cycling, or the like. FIG. 4E includes agraph that illustrates mean power frequency (i.e., MPF) versus time,where the MPF may be a mean power frequency variance observed during amuscleprint exercise routine such as “step-up” routine or weightliftingroutine, or the like.

Additionally, the muscleprint protocol can obtain data that is thenprocessed by a frequency-based amplitude adjusted RMS (FBAAR) process tocreate a standardized profile for an individual. The data can then beused to compare the beginning rectified amplitude values to the endingrectified amplitude values across time. For instance, a user may be ableto make comparisons over the course of a particular period of time(e.g., 30 minute run) in which it is known that amplitude drop-offoccurs despite speed/stride rate/incline being held constant (see FIG.4F). FIG. 4F includes a graph that illustrates RMS sEMG versus time orfrequency-based, amplitude-adjusted RMS sEMG versus time (i.e., FBAARversus time) during a muscleprint exercise routine such as walking,jogging, running, cycling, or the like as well as noncontinuous muscleactivities.

Additionally, the FBAAR process can be implemented with or substitutedwith time-based amplitude adjusted RMS (TBAAR). The TBARR issubstantially similar to FBAAR in application to the invention describedherein. As such, the amplitude adjustments can be made with any basis inaddition to frequency and time. Any appropriate parameter may beamplitude adjusted using RMS. Thus, recitation herein of frequency-basedamplitude adjusted RMS (FBAAR) process can also refer to TBAAR or other.

In one embodiment, the muscleprinting protocol can be implemented withcomputing devices and software. The computing device can be associatedwith sensors that are coupled to subject's body at particular locations.The sensors can be placed on the skin adjacent to one or more muscles tobe monitored and assessed during the protocol. The sensor can becommunicatively coupled, either wired or wireless, so a computing systemhaving the software that can operate the method. The computing systemcan receive and record the data. The computing system, viamuscleprinting protocol software, can process data from the sensors. Thecomputing system can then generate a viewable format of the data foranalysis by the subject. Additionally, the computing system can access adatabase over a network in order to obtain comparative data for one ormore other users or to provide the subject's data to the database. Thedata from the database can be selectively filtered to identify one ormore subjects that the subject may want to compare their data with. Theother subjects may be persons known or unknown to the current subjectundergoing the muscleprint. A viewable representation of the data, suchas a graph, can then be generated to compare the current subject withone or more other subjects. The data of the current subject can also beprovided to the database and stored, which data can then be accessed byother subjects for their own comparative analysis. Thus, themuscleprinting protocol can utilize computer hardware and/or software toautomatically compare a subject's muscle response profile to a largedatabase of muscle responses in order to categorize the subject's musclefitness level. The protocol can also provide tailored exercise plansbased on which muscles the subject could train for improvement. Theprotocol can also provide recommendations to a particular subject fortraining method to optimize muscle activity performance given theirparticular profile.

FIG. 13 illustrates an embodiment of a muscleprint protocol 100. Such amuscleprint protocol 100 can include: attaching one or more surfaceelectromyometry (sEMG) sensors to the skin of a subject so as to beoperably coupled with one or more muscles of the subject (“Attach SensorTo Skin,” block 110); operably coupling the one or more sEMG sensors toa computing system (“Link Sensor To Computer,” block 112); performingthe predetermined muscle activity of a muscleprint protocol (“PerformMuscleprint Protocol,” block 114), wherein in the muscleprint protocolthe one or more sensors each monitor muscle sEMG data of the one or moremuscles while the subject performs during the predetermined activity inorder to determine the subject's muscular capabilities of the one ormore muscles over a defined period of time or portion thereof;monitoring and/or recording sEMG data of the one or more muscles duringthe predetermined muscle activity (“Monitor/Record sEMG Data,” block116); and providing the sEMG data to the subject such that the subjectcan improve muscle performance for the predetermined muscle activity byusing the sEMG data (“Provide sEMG Data to Subject,” block 118).

In one embodiment, the muscleprint protocol can include determiningand/or generating a muscle sEMG profile in response to the predeterminedmuscle activity over the defined period of time or portion thereof.

In one embodiment, the muscleprint protocol can include a step-up testthat incrementally increases muscle output or muscle effort over one ormore step-up time periods of the predetermined muscle activity until thesubject is sufficiently fatigued or predetermined muscle activity timeperiod or predetermined repetitions of the muscle activity.

In one embodiment, the muscleprint protocol can include graphing themuscleprint protocol with sEMG data versus time, and providing the graphto the subject.

In one embodiment, the muscleprint protocol can include accessing sEMGdata of one or more other subjects from a database, and comparing thesubject's sEMG data with the sEMG data of the other subjects from thedatabase.

In one embodiment, the muscleprint protocol can include: filtering theone or more subjects from the database based on one or more criteria;providing sEMG data of the filtered one or more subjects to thecomputing system; and generating a graph of the subject's sEMG data withthe sEMG data of the filtered one or more subjects.

The muscleprint protocol can be implemented as part of any of the otherprotocols described herein. Also, the method steps of the muscleprintprotocol can be illustrated as a flowchart or the like.

Stride Rate Tuning

One of the reasons people exercise is due to the energy consumption bythe body in order to perform an athletic activity. The energyconsumption of exercise can be used for maintaining or improving asubject's physical attributes. During exercise, muscle contractionconsumes energy. The more a muscle is contracted, the greater the energyconsumption, which can be measured in calories. The energy consumptioncan also be expressed as work done by the muscle, and the more work doneby the muscle does, the greater the energy consumption and greateramounts of calories are burned. Stride rate tuning can be used for anycontinuous muscle activity. Stride rate tuning can also be used fornoncontinuous muscle activities when each repetition is described as astride in accordance with the parameters herein.

Running is performed by contracting muscles during a stride. The rate atwhich a subject runs can be measured by the distance that is covered ina certain period of time. The subject's stride can be measured in termsof a stride rate that is the number of heel-strikes in a minute. Forcycling, the stride can be measured in terms of when the peddle is atits lowest point. A heal-strike can be described as a beat, and thenumber of strikes over time can have a strike rate that can be describedas “beats per minute” or “BPM.” Also, stride length can be described asthe distance covered in a single step by a runner. For cycling, thestride length can be the distance covered between peddle low points. Itshould also be noted that stride rate is not equivalent to speed. At agiven constant speed, a subject may run at a variety of stride rates. Infact, for each athlete, there is a definite range of stride rates at anygiven speed. Also, runners are usually aware of a so-called “naturalstride rate,” even if they do not call it that, that they feelcomfortable using at any given speed. FIG. 5A includes a schematicrepresentation of an exercise routine that is measured at stride lengthversus speed versus stride rate, wherein the stride length is measuredas distance between right foot heal-strikes of a single stride. FIG. 5Bincludes a schematic representation of an exercise routine that ismeasured at half strides or for each heal strike of both feet. Thestride length is the distance between a first left or left footheel-strike and a second right or left foot-heel strike, where only onefoot is considered, which can be either the right foot or left foot asillustrated in FIG. 5A. The average speed can be determined byidentifying the total distance (Dtot) traveled, which is divided by thetotal time. The total time can be determined by a final time (Tf)subtracted by the initial time (To). Equation 1 defines average speed.

Average Speed=Dtot/(Tf−To)  Equation 1

The stride rate can be determined by using the heel-strikes of both theleft and right foot. The total number of heel-strikes per minute equalsthe stride rate, which can be measured in beats per minute (BPM), whichcan be audible. It may also be referred to as heel-strikes per minute(hspm). Dividing the stride rate by two can provide the haploid striderate, which is for one side of the body, right or left, which is shownin Equation 2.

Haploid Stride Rate=(Stride Rate)/2  Equation 2

In the example illustrated in FIG. 5B, there are a total of 60heel-strikes in 60 seconds, with one heel-strike per second. As such,the stride rate is 60 BPM (or hspm). The stride length cannot bedetermined from stride rate alone. Some form of distance information isneeded for the calculation. The distance information, for example, caninclude stride length, total stride distance traveled, or other.

Different stride rates have different cumulative energy costs. Acumulative energy cost can be defined as being proportional to the sumof integrated rectified sEMG observed in major muscles being used for anactivity. Equation 3 illustrates a calculation of a cumulative energycost (CEC) for muscles that may be used for running, which can include:right quadriceps (A); left quadriceps (B); right hamstring (C); lefthamstring (D); right calf (E); left calf (F); abdominal (G); and lowerback (H). For example, for running, the cumulative energy cost could beproportional to the sum of the areas under the curves of rectified sEMGgraphs recorded in the Left Quadriceps Femoris, Right QuadricepsFemoris, Left Hamstring, Right Hamstring, Left Gastrocnemius, and RightGastrocnemius as shown in Equation 3. These muscles can each have inindividual sensor associated therewith. However, the relationship can besimplified by selecting particular muscles as shown in Equations 4 or 5,which are only examples. Any muscle or group of muscles can beconsidered or excluded as, desired. The area under the curve can then beused to calculate the calorie cost by using a skeletal muscle calorieindex (SMCI).

CEC∝∫A+∫B+∫C+∫D+∫E+∫F+∫G+∫H  Equation 3

CEC∝∫A+∫D+∫E+∫H  Equation 4

CEC∝∫A+∫B+∫C+∫D+∫E+∫F  Equation 5

The SMCI can also be used as an adjustment to methods of calorieestimation currently in use which are based on heart rate. The SMCIadjustment can be used to improve the accuracy of the calculated calorieburn rate based on HR-only methods.

The stride rate can be used for stride rate tuning. Stride rate tuning(SRT) is can be described as a protocol for optimization stride rate ofa subject based on sEMG data. The optimization of stride rate can beused to minimize energy expenditure during activities. There are variousways to implement SRT, one of which involves running at a constantspeed. First, the runner applies sensors to their quads, hamstrings, andcalves as well as other muscles such as those recited above (e.g., L andR leg muscles). A computing system having hardware and software can beprogramed to calculate the sum of the integrated sEMG amplitudes of all6 muscles being monitored to determine the SEC. Then the runner beginsto run at a constant rate. This can be done on a treadmill, or outsidewith some device that allows the runner to maintain their speed at asubstantially constant rate. A secondary speed monitor can be used bythe runner. A secondary speed monitor can include another object, suchas a motorcycle, moped, car, bike or the like, that can operate at aconstant speed, or use of a speedometer device that provides speed(e.g., audio or visual speed information) to the runner so that therunner can modulate their running to maintain the speed. During SRT, therunner should be on a flat or horizontal surface, or on a slope orincline that is substantially constant. The runner can run for a setduration (e.g., run for 20 minutes) to allow the observed rectified sEMGamplitude to level off, which can eliminate the need for FBAARadjustment or any other amplitude adjusted RMS process, such as TBAAR.Then the stride rate is then varied, from the low limit of the runner'sstride range to the high limit of the runner's stride range, in regularincrements (see FIGS. 6A-6B).

For an example of SRT, the runner performs the following: 20 minutes ofnatural stride rate as a warm up; then 1 minute of running at 110 BPM;then 1 minute or running at 115 BPM; then 1 minute or running at 120BPM; and so on up to resulting 1 minute of running at 190 BPM or maximumBPM for the runner. FIG. 6A includes a graph that illustrates striderate versus time, where speed is constant throughout exercise routine at5.5 MPH, where stride rate is held constant up to 20 minutes and theninitially decreased before being increased in a step-up test. For thisrunner, 110-160 RPM is a stride rate range, and 130 BPM wasself-identified as a “natural stride rate.”

At the conclusion of the run, each increment has an associatedcombination rectified sEMG integral (e.g., area under the rectified sEMGcurve for that increment for each muscle, then all muscles' integralsare added together) as shown in Equation 6, using the abbreviations forthe leg muscles as shown above to calculate the cumulative integral(CI). The CI is then plotted verses time. Since the areas under thecurves are proportional to the energy cost, the computing system candetermine energy cost of different stride rates, and prepare graphicalrepresentations thereof (see FIG. 6B). FIG. 6B includes a graph thatillustrates cumulative integral versus time for FIG. 6A, where speed isconstant throughout exercise routine at 5.5 MPH in a “warm-up period.”At 135 BPM, primary trough/valley observed, which is compared to the 130self-identified “natural stride rate.” At 155 BPM, secondarytrough/valley observed, which is useful for running on an incline.Typical response profile for this type of graph is a “U” or “V” shapedcurve.

CI=∫A+∫B+∫C+∫D+∫E+∫F

The low-point on the graph of FIG. 6B corresponds to a stride rate whichresults in the smallest possible additive integral. This stride rate maynot be equivalent to the stride rate that a user thinks of as their“natural stride rate”. However, it is the stride rate which results inthe smallest caloric burn rate, and as such is a singularly useful pieceof information for competitive runners and can be referred to as thetrue natural stride rate. For noncontinuous muscle activities, arepetition can be considered to be a stride, and the method can beimplemented for repetitions in place of strides. Thus, stride can alsorefer to repetitions of a muscle activity, such as weight lifting orarrow firing repetitions.

FIG. 14 illustrates an embodiment of performing a muscle improvementprotocol 200 can include: attaching one or more surface electromyometry(sEMG) sensors to the skin of a subject so as to be operably coupledwith one or more muscles of the subject (“Attach Sensor To Skin,” block210); operably coupling the one or more sEMG sensors to a computingsystem (“Link Sensor to Computer,” block 212); performing thepredetermined muscle activity of a stride rate tuning protocol (“PerformStride Rate Tuning Protocol,” block 214), wherein in the stride ratetuning protocol the one or more sensors monitor muscle sEMG data whilethe subject adjusts their caloric consumption during a controlledactivity based on sEMG data that is measured and/or analyzed, and thesEMG data is provided to the subject in order to facilitate theadjustment of caloric consumption; monitoring and/or recording sEMG dataof the one or more muscles during the predetermined muscle activity(“Monitor/Record sEMG Data,” block 216); and providing the sEMG data tothe subject such that the subject can improve muscle performance for thepredetermined muscle activity by using the sEMG data (“Provide sEMG Datato Subject,” block 218). The muscle improvement protocol can alsoinclude determining one or more of a stride; stride rate; natural striderate; haploid stride rate; stride distance; or combination thereof.Also, the subject's true natural stride rate can be determined.

In one embodiment, the muscle improvement protocol can includedetermining cumulative energy cost for the one or more muscles. Thisinformation can then be used for optimizing stride rate for the subjectbased on sEMG data so as to minimize energy consumption by the one ormore muscles.

In one embodiment, the muscle improvement protocol can include:performing the predetermined muscle activity at an initial constant rateor load for a predetermined time period or until exhaustion or untilsEMG amplitude levels; performing the predetermined muscle activity at alow constant rate or load that is lower than the initial constant rateor load; and incrementally increasing the rate or load of thepredetermined muscle activity at incremental time periods. The muscleimprovement protocol can include the initial constant rate beingsubstantially the subject's natural stride rate or estimate thereof.

In one embodiment, the muscle improvement protocol can include:computing energy costs of different stride rates; and providing thecomputed energy costs to the subject.

The stride rate protocol can be implemented as part of any of the otherprotocols described herein. Also, the method steps of the stride rateprotocol can be illustrated as a flowchart or the like.

Controlled Activity Training (CAT)

Additionally, sEMG data can be used in controlled activity training forimprovement of muscle function and endurance. Controlled activitytraining (CAT) refers to performing an activity with some manner ofcontrol with regard to sEMG data. In one instance, sEMG data is providedto the subject so that they can modulate their muscle activity in orderto maintain or attempt to maintain the sEMG data at a certain level. Inanother instance, it includes using sEMG data to determine at what timepoint during a muscle activity fatigue sets in that reduces caloricconsumption, and then the subject attempts maximum muscle activityoutput for a period up to the time point when muscle activity fatiguebegins to set in. In both cases, muscle activity is controlled by use ofsEMG data. As such, the sEMG data can include control variables asfollows: sEMG amplitude; integrated sEMG; MPF; and muscle fatigue onsetindex (MFOI). The subject can then use these control variables in orderto modulate the muscle activity, which can include modulating thefollowing dependent variables: speed; stride rate; stroke rate(swimming); or weight lifted. Of course, the muscle activity that is adependent variable will depend on the type of physical activity.

For example, it has been observed that when running for certain time(e.g., 30 minutes), the amplitude of rectified sEMG observed in majormuscle groups of the lower extremities initially demonstrates a largepeak which decreases over the course of the first period (e.g., 10-20minutes) of the run, but which can vary depending on the subject (seeFIG. 7A). FIG. 7A includes a graph that illustrates sEMG amplitudeversus time or speed versus time, where speed is constant throughoutexercise routine. Then, the amplitude continues to decrease thereafteruntil the end of the run, but at a much slower rate of decrease. Thefirst period (e.g., 12 minutes) of the run have a greater caloric costthan the remainder of the run. The rectified sEMG amplitude, however,can be reduced by reducing the speed of the run. If the runner's speedis allowed to be variable, and instead hold the rectified sEMG amplitudeconstant (e.g., at whatever level is observed toward the end of aninitial calibration run), the runner's speed would start out slow, andgradually speed up as their muscles physical properties changed over thecourse of the run. This specific implementation of CAT is called DelayedFatigue Onset Training (DFOT). DFOT is a process which realizes at itscore that the energy available to an individual during an activity islimited. The calories available to that individual are limited. Thetotal work that the individual can do during the activity is limited.Since energy expenditure is proportional to sEMG output, by reducing theearly-stage sEMG output, the runner can reduce the high caloric cost ofthe first period (e.g., 12 minutes) of a run. These calories aretherefore available to the runner at the end of the run (see FIG. 7B).FIG. 7B includes a graph that illustrates sEMG amplitude versus time orspeed versus time, where speed is controlled to keep sEMG amplitudeunder a limit throughout exercise routine, and exhaustion is delayed.

While DFOT is one type of CAT, the subject may also take the oppositeapproach, and design a CAT focused on maximizing caloric burn withrespect to time. A runner who is interested in burning as many caloriesas quickly as possible or having a goal of weight loss and fitness, orshort muscle activity competitive performance, but not endurance, mightbe interested in a CAT structured as follows. The runner goes on initialcalibration run and the sEMG amplitude is measured. The inflection pointis measured, and the time to the inflection point is saved. On the nextrun, the runner warms up with muscle groups other than those of theirlower extremities (some weight-lifting, for instance, to get the heartrate elevated for ten minutes prior to the run). Then, the runnerengages in interval training where the length of the intervals areequivalent to the length of time until the inflection point. Let usassume for example that the inflection point is located at 12 minutes.The runner would be instructed to run near their maximum comfortablespeed for 12 minutes, without the benefit of accelerating into thatspeed.

Next, the runner takes a break for ten minutes, perhaps working out withdifferent exercises (weight-lifting). Then, the runner goes back andruns another interval period (e.g., 12 minutes) at a fast pace. Eachtime the runner performs the interval run, they can maximize caloricconsumption by starting the muscle activity of running as hard and fastas possible for the first period (e.g., 12 minutes), and then doing adifferent activity after the first period and/or between running periodswhen the amplitude starts to drop and caloric burn rate decreases (seeFIG. 8A).

FIG. 8A includes a graph that illustrates sEMG amplitude versus time fora set time of consistent exercise (e.g., running etc.) followed by restor non-exercise, where an inflection point is identified. In thisfigure, the runner runs at a solid effort for 30 minutes, followed bysome period of rest before again running solid for another period oftime.

Also, these CAT protocols can be performed with any muscle activity.Weightlifting is an example of a noncontinuous muscle activity. FIG. 8Bincludes a graph that illustrates sEMG amplitude versus time for a settime of consistent exercise (e.g., weight lifting or other periodicexercise) followed by rest or non-exercise, which is shown asexercise-rest-exercise-rest-exercise. FIG. 8C includes a graph thatillustrates sEMG amplitude versus time for a set time of consistentexercise (e.g., weight lifting or other periodic exercise) followed byrest or non-exercise, which is shown asexercise-rest-exercise-rest-exercise. FIG. 8C is an alternative profilecompared to FIG. 8B, where FIG. 8B shows a rounded profile indicative ofa extending the set past the maximum, FIG. 8C show that the set isterminated at the maximum.

Additionally, another CAT protocol for DFOT can be implemented asfollows. The runner first goes on a calibration run for a first periodof time (e.g., 12 minutes) in which the rectified sEMG amplitude ismeasured and the inflection point is identified. The inflection pointmarks a change from initial high-amplitude levels to post first period(e.g., post-12-minute) lower-amplitude levels. The amplitude at theinflection point is measured, and the final amplitude is measured, aswell as at any time point therebetween. The average amplitude iscalculated for the post-inflection point data. The average amplitudelevel (post-inflection) is recorded and may be analyzed and/or graphedor otherwise provided to the runner. The runner than goes on anotherrun, and uses the average amplitude level that is saved as the maximumallowable amplitude level for the whole run. Accordingly, amplitude isheld constant or substantially constant during the whole next run. Ifthe amplitude is too high, the runner's speed can be decremented orotherwise reduce until the amplitude is below the maximum allowableamplitude level (e.g., safety limit). Amplitude being lower than thelimit is permissible.

FIG. 15 illustrates an embodiment of a muscle improvement protocol 300,which can include: attaching one or more surface electromyometry (sEMG)sensors to the skin of a subject so as to be operably coupled with oneor more muscles of the subject (“Attach Sensor to Skin,” block 310);operably coupling the one or more sEMG sensors to a computing system(“Link Sensor to Computer,” block 312); performing the predeterminedmuscle activity of a controlled activity training protocol (“PerformControlled Activity Training Protocol,” block 314), wherein in thecontrolled activity training protocol the subject maintainssubstantially a constant sEMG metric or metric derivative or metricintegral by varying muscle activity exertion during the predeterminedmuscle activity; monitoring and/or recording sEMG data of the one ormore muscles during the predetermined muscle activity (“Monitor/RecordsEMG Data,” block 316); and providing the sEMG data to the subject suchthat the subject can improve muscle performance for the predeterminedmuscle activity by using the sEMG data (“Provide sEMG Data to Subject,”block 318).

In one embodiment, the muscle improvement protocol can include:analyzing the sEMG data; and determining a fatigue initiation time pointat which fatigue initiates after an initial time period.

In one embodiment, the muscle improvement protocol can includeperforming the predetermined muscle activity again for a time periodless than the initial time period so that the subject ceases performanceof the predetermined muscle activity before the fatigue initiation timepoint. This can include controlling a second performance of thepredetermined muscle activity based on sEMG data collected during afirst performance of the predetermined muscle activity.

In one embodiment, the muscle improvement protocol can include: holdingsubstantially constant for control variables selected from sEMGamplitude, integrated sEMG, MPF, and MFOI; and varying performance ofthe predetermined muscle activity at the substantially constant controlvariable. The muscle improvement protocol can also include performing adelayed fatigue onset training protocol.

In one embodiment, the muscle improvement protocol can include:performing a calibration protocol for the predetermined muscle activity;determining an inflection point of sEMG data during the calibrationprotocol, wherein the inflection point identifies an activity periodfrom beginning the calibration protocol to a fatigue time point; andperforming the predetermined muscle activity for the activity period oneor more times. Also, prior to performance of the predetermined muscleactivity after the calibration protocol, the subject can warm up withmuscle groups other than involved in the predetermined muscle activity.The activity period can be performed at a maximum effort that can besubstantially sustained for the duration of the activity period.Activity between the different activity periods can include eitherresting or performing a muscle activity different from the predeterminedmuscle activity for a rest period between repetitions of thepredetermined muscle activity. Activity during the activity period canbe performed so as to maximize caloric consumption during the activityperiod.

In one embodiment, the muscle improvement protocol can include:measuring sEMG amplitude at inflection point; measuring final amplitudeof predetermined muscle activity; calculating average sEMG amplitude forpost-inflection point data; and performing the predetermined muscleactivity another time while holding the sEMG amplitude substantiallyconstant.

The controlled activity protocol can be implemented as part of any ofthe other protocols described herein. Also, the method steps of thecontrolled activity training protocol can be illustrated as a flowchartor the like.

Frequency-Based, Amplitude-Adjusted Root Mean Square (FBAAR)

It has been experimentally observed that when a subject exercises for along period of time (e.g., t>10 minutes) there is noticeable sEMGamplitude drop-off which occurs in the rectified sEMG signals of theirmuscles (see FIGS. 10A-10C. For example, if someone runs for a period oftime (e.g., 30 minutes), the amplitude of rectified sEMG observed willdecrease noticeably over this period of time. In one aspect, it can beuseful to adjust the amplitude of the rectified signal so that thisdecrease is cancelled out. This can be done by providing the sEMG datato the subject so that they can module effort. The amplitude drop-offcorrelates with muscle fatigue (e.g., compression of power spectrum),though the rate of fatigue, and the correlation, is subject-specific.

FIG. 10A includes a graph similar to FIG. 8A, which shows the sEMGamplitude profile. FIG. 10B includes a graph that illustrates sEMGamplitude versus frequency for a non-fatigued muscle spectrum from FIG.10A, and shows the MPF. FIG. 10C includes a graph that illustrates sEMGamplitude versus frequency for a fatigued muscle spectrum from FIG. 10A,and shows the MPF.

Also, a FBAAR muscle activity protocol can include a subject firstperforming a typical exercise, and the computing system establishes thecorrelation between degree of amplitude drop-off over time, and thecorresponding MPF (see FIG. 9A). Then, in the future, when the subjectperforms similar types of exercises, the computing system can measure ordetermine the MPF for the subject, and the subject can modulate theirmuscle activity in order to adjust the signal accordingly (see FIG. 9B).This provides the subject with a way to observe the amplitude levelsthat would be observed if the subject were always minimally fatiguedwith respect to the muscle potential. When attempting to compare andcorrelate amplitude levels for a subject over time, or over multipledays, this muscle activity protocol can be useful for thestandardization and comparison of amplitude of values.

The FBAAR muscle activity protocol can improve fitness and endurance,and can be used to help a subject to delay the onset of fatigue. Byrepeating the protocol, a subject can extend the period time they canexercise before the onset of fatigue. The computing system can implementalgorithms in order to make use of metrics, which are provided to thesubject during the protocol so that they can adjust their muscleactivity output.

In one embodiment, a muscle assessment protocol can include: attachingone or more surface electromyometry (sEMG) sensors to the skin of asubject so as to be operably coupled with one or more muscles of thesubject; operably coupling the one or more sEMG sensors to a computingsystem; performing the predetermined muscle activity of anamplitude-adjusted root mean square protocol, wherein in thefrequency-based, amplitude-adjusted root mean square that includesdisplaying sEMG data that is adjusted to compensate for muscle fatigueof the one or more muscles; monitoring and/or recording sEMG data of theone or more muscles during the predetermined muscle activity; andproviding the sEMG data to the subject such that the subject can improvemuscle performance for the predetermined muscle activity by using thesEMG data. Also, the protocol can include: providing an sEMG metric tothe subject during the predetermined muscle activity; and modulatingeffort by the subject during the predetermined muscle activity so as tomaintain the sEMG metric at substantially a constant.

The FBAAR muscle activity protocol can be implemented as part of any ofthe other protocols described herein. Also, the method steps of theFBAAR muscle activity protocol can be illustrated as a flowchart or thelike.

In one embodiment, the invention described herein can be implementedwith the sensors or systems described in U.S. Provisional ApplicationNos. 61/385,048 and 61/514,148 and U.S. patent application Ser. No.______ (Attorney Docket Number S1061.10011US02, the serial number to beinserted here after the filing thereof). Additionally, the inventiondescribed herein can be implemented with metrics and algorithmsdescribed in U.S. Provisional Application No. 61/385,038 and U.S. patentapplication Ser. No. ______ (Attorney Docket Number S1061.10009US02, theserial number to be inserted here after the filing thereof). Also, theinvention described herein can be implemented with methods of promotingfitness described in U.S. Provisional Application No. 61/385,053 andU.S. patent application Ser. No. ______ (Attorney Docket NumberS1061.10014US02, the serial number to be inserted here after the filingthereof). Further, the invention described herein can be implementedwith graphing methods described in U.S. Provisional Application No.61/385,049. Also, the invention described herein can be implemented withthe multi-functional carrying case and associated biometric sensors andtransceivers described in U.S. Provisional Application No. 61/385,051.The invention described herein can be implemented with the devices,systems, and/or methods described in U.S. Pat. Nos. 7,593,769 and7,809,435. The patents and patent applications recited herein areincorporated herein by specific reference in their entirety.

One skilled in the art will appreciate that, for this and otherprocesses and methods disclosed herein, the functions performed in theprocesses and methods may be implemented in differing order.Furthermore, the outlined steps and operations are only provided asexamples, and some of the steps and operations may be optional, combinedinto fewer steps and operations, or expanded into additional steps andoperations without detracting from the essence of the disclosedembodiments. The methods can also be implemented with hardware and/orsoftware on the sensors and/or computing system.

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its spirit and scope, as will be apparentto those skilled in the art. Functionally equivalent methods andapparatuses within the scope of the disclosure, in addition to thoseenumerated herein, will be apparent to those skilled in the art from theforegoing descriptions. Such modifications and variations are intendedto fall within the scope of the appended claims. The present disclosureis to be limited only by the terms of the appended claims, along withthe full scope of equivalents to which such claims are entitled. It isalso to be understood that the terminology used herein is for thepurpose of describing particular embodiments only, and is not intendedto be limiting.

In one embodiment, the present methods can include aspects performed ona computing system. As such, the computing system can include a memorydevice that has the computer-executable instructions for performing themethod. The computer-executable instructions can be part of a computerprogram product that includes one or more algorithms for performing anyof the methods of any of the claims.

In one embodiment, any of the operations, processes, methods, or stepsdescribed herein can be implemented as computer-readable instructionsstored on a computer-readable medium. The computer-readable instructionscan be executed by a processor of a wide range of computing systems fromdesktop computing systems, portable computing systems, tablet computingsystems, and hand-held computing systems as well as any other computingdevice.

There is little distinction left between hardware and softwareimplementations of aspects of systems; the use of hardware or softwareis generally (but not always, in that in certain contexts the choicebetween hardware and software can become significant) a design choicerepresenting cost versus efficiency tradeoffs. There are variousvehicles by which processes and/or systems and/or other technologiesdescribed herein can be effected (e.g., hardware, software, and/orfirmware), and that the preferred vehicle will vary with the context inwhich the processes and/or systems and/or other technologies aredeployed. For example, if an implementer determines that speed andaccuracy are paramount, the implementer may opt for a mainly hardwareand/or firmware vehicle; if flexibility is paramount, the implementermay opt for a mainly software implementation; or, yet againalternatively, the implementer may opt for some combination of hardware,software, and/or firmware.

The foregoing detailed description has set forth various embodiments ofthe processes via the use of block diagrams, flowcharts, and/orexamples. Insofar as such block diagrams, flowcharts, and/or examplescontain one or more functions and/or operations, it will be understoodby those within the art that each function and/or operation within suchblock diagrams, flowcharts, or examples can be implemented, individuallyand/or collectively, by a wide range of hardware, software, firmware, orvirtually any combination thereof. In one embodiment, several portionsof the subject matter described herein may be implemented viaApplication Specific Integrated Circuits (ASICs), Field ProgrammableGate Arrays (FPGAs), digital signal processors (DSPs), or otherintegrated formats. However, those skilled in the art will recognizethat some aspects of the embodiments disclosed herein, in whole or inpart, can be equivalently implemented in integrated circuits, as one ormore computer programs running on one or more computers (e.g., as one ormore programs running on one or more computer systems), as one or moreprograms running on one or more processors (e.g., as one or moreprograms running on one or more microprocessors), as firmware, or asvirtually any combination thereof, and that designing the circuitryand/or writing the code for the software and or firmware would be wellwithin the skill of one of skill in the art in light of this disclosure.In addition, those skilled in the art will appreciate that themechanisms of the subject matter described herein are capable of beingdistributed as a program product in a variety of forms, and that anillustrative embodiment of the subject matter described herein appliesregardless of the particular type of signal hearing medium used toactually carry out the distribution. Examples of a signal bearing mediuminclude, but are not limited to, the following: a recordable type mediumsuch as a floppy disk, a hard disk drive, a CD, a DVD, a digital tape, acomputer memory, etc.; and a transmission type medium such as a digitaland/or an analog communication medium (e.g., a fiber optic cable, awaveguide, a wired communications link, a wireless communication link,etc.). Those skilled in the art will recognize that it is common withinthe art to describe devices and/or processes in the fashion set forthherein, and thereafter use engineering practices to integrate suchdescribed devices and/or processes into data processing systems. Thatis, at least a portion of the devices and/or processes described hereincan be integrated into a data processing system via a reasonable amountof experimentation. Those having skill in the art will recognize that atypical data processing system generally includes one or more of asystem unit housing, a video display device, a memory such as volatileand non-volatile memory, processors such as microprocessors and digitalsignal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one ormore interaction devices, such as a touch pad or screen, and/or controlsystems including feedback loops and control motors (e.g., feedback forsensing position and/or velocity; control motors for moving and/oradjusting components and/or quantities). A typical data processingsystem may be implemented utilizing any suitable commercially availablecomponents, such as those generally found in datacomputing/communication and/or network computing/communication systems.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that in fact many other architectures can beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected”, or“operably coupled”, to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably couplable”, to each other to achieve the desiredfunctionality. Specific examples of operably couplable include but arenot limited to physically mateable and/or physically interactingcomponents and/or wirelessly interactable and/or wirelessly interactingcomponents and/or logically interacting and/or logically interactablecomponents.

FIG. 11 shows an example computing device 600 that is arranged toperform any of the computing methods described herein. In a very basicconfiguration 602, computing device 600 generally includes one or moreprocessors 604 and a system memory 606. A memory bus 608 may be used forcommunicating between processor 604 and system memory 606.

Depending on the desired configuration, processor 604 may be of any typeincluding but not limited to a microprocessor (μP), a microcontroller(μC), a digital signal processor (DSP), or any combination thereof.Processor 604 may include one more levels of caching, such as a levelone cache 610 and a level two cache 612, a processor core 614, andregisters 616. An example processor core 614 may include an arithmeticlogic unit (ALU), a floating point unit (FPU), a digital signalprocessing core (DSP Core), or any combination thereof. An examplememory controller 618 may also be used with processor 604, or in someimplementations memory controller 618 may be an internal part ofprocessor 604.

Depending on the desired configuration, system memory 606 may be of anytype including but not limited to volatile memory (such as RAM),non-volatile memory (such as ROM, flash memory, etc.) or any combinationthereof. System memory 606 may include an operating system 620, one ormore applications 622, and program data 624. Application 622 may includea determination application 626 that is arranged to perform thefunctions as described herein including those described with respect tomethods described herein. Program Data 624 may include determinationinformation 628 that may be useful for analyzing the contaminationcharacteristics provided by the sensor unit 240. In some embodiments,application 622 may be arranged to operate with program data 624 onoperating system 620 such that the work performed by untrusted computingnodes can be verified as described herein. This described basicconfiguration 602 is illustrated in FIG. 6 by those components withinthe inner dashed line.

Computing device 600 may have additional features or functionality, andadditional interfaces to facilitate communications between basicconfiguration 602 and any required devices and interfaces. For example,a bus/interface controller 630 may be used to facilitate communicationsbetween basic configuration 602 and one or more data storage devices 632via a storage interface bus 634. Data storage devices 632 may beremovable storage devices 636, non-removable storage devices 638, or acombination thereof. Examples of removable storage and non-removablestorage devices include magnetic disk devices such as flexible diskdrives and hard-disk drives (HDD), optical disk drives such as compactdisk (CD) drives or digital versatile disk (DVD) drives, solid statedrives (SSD), and tape drives to name a few. Example computer storagemedia may include volatile and nonvolatile, removable and non-removablemedia implemented in any method or technology for storage ofinformation, such as computer readable instructions, data structures,program modules, or other data.

System memory 606, removable storage devices 636 and non-removablestorage devices 638 are examples of computer storage media. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical storage, magnetic cassettes, magnetic tape, magneticdisk storage or other magnetic storage devices, or any other mediumwhich may be used to store the desired information and which may beaccessed by computing device 600. Any such computer storage media may bepart of computing device 600.

Computing device 600 may also include an interface bus 640 forfacilitating communication from various interface devices (e.g., outputdevices 642, peripheral interfaces 644, and communication devices 646)to basic configuration 602 via bus/interface controller 630. Exampleoutput devices 642 include a graphics processing unit 648 and an audioprocessing unit 650, which may be configured to communicate to variousexternal devices such as a display or speakers via one or more A/V ports652.

Example peripheral interfaces 644 include a serial interface controller654 or a parallel interface controller 656, which may be configured tocommunicate with external devices such as input devices (e.g., keyboard,mouse, pen, voice input device, touch input device, etc.) or otherperipheral devices (e.g., printer, scanner, etc.) via one or more I/Oports 658. An example communication device 646 includes a networkcontroller 660, which may be arranged to facilitate communications withone or more other computing devices 662 over a network communicationlink via one or more communication ports 664.

The network communication link may be one example of a communicationmedia. Communication media may generally be embodied by computerreadable instructions, data structures, program modules, or other datain a modulated data signal, such as a carrier wave or other transportmechanism, and may include any information delivery media. A “modulateddata signal” may be a signal that has one or more of its characteristicsset or changed in such a manner as to encode information in the signal.By way of example, and not limitation, communication media may includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), microwave,infrared (TR) and other wireless media. The term computer readable mediaas used herein may include both storage media and communication media.

Computing device 600 may be implemented as a portion of a small-formfactor portable (or mobile) electronic device such as a cell phone, apersonal data assistant (PDA), a personal media player device, awireless web-watch device, a personal headset device, an applicationspecific device, or a hybrid device that include any of the abovefunctions. Computing device 600 may also be implemented as a personalcomputer including both laptop computer and non-laptop computerconfigurations. The computing device 600 can also be any type of networkcomputing device. The computing device 600 can also be an automatedsystem as described herein.

The embodiments described herein may include the use of a specialpurpose or general-purpose computer including various computer hardwareor software modules.

Embodiments within the scope of the present invention also includecomputer-readable media for carrying or having computer-executableinstructions or data structures stored thereon. Such computer-readablemedia can be any available media that can be accessed by a generalpurpose or special purpose computer. By way of example, and notlimitation, such computer-readable media can comprise RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium which can be used to carryor store desired program code means in the form of computer-executableinstructions or data structures and which can be accessed by a generalpurpose or special purpose computer. When information is transferred orprovided over a network or another communications connection (eitherhardwired, wireless, or a combination of hardwired or wireless) to acomputer, the computer properly views the connection as acomputer-readable medium. Thus, any such connection is properly termed acomputer-readable medium. Combinations of the above should also beincluded within the scope of computer-readable media.

Computer-executable instructions comprise, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. Although the subject matter has been described inlanguage specific to structural features and/or methodological acts, itis to be understood that the subject matter defined in the appendedclaims is not necessarily limited to the specific features or actsdescribed above. Rather, the specific features and acts described aboveare disclosed as example forms of implementing the claims.

As used herein, the term “module” or “component” can refer to softwareobjects or routines that execute on the computing system. The differentcomponents, modules, engines, and services described herein may beimplemented as objects or processes that execute on the computing system(e.g., as separate threads). While the system and methods describedherein are preferably implemented in software, implementations inhardware or a combination of software and hardware are also possible andcontemplated. In this description, a “computing entity” may be anycomputing system as previously defined herein, or any module orcombination of modulates running on a computing system.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for sakeof clarity.

It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to embodiments containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should be interpreted to mean “at least one”or “one or more”); the same holds true for the use of definite articlesused to introduce claim recitations. In addition, even if a specificnumber of an introduced claim recitation is explicitly recited, thoseskilled in the art will recognize that such recitation should beinterpreted to mean at least the recited number (e.g., the barerecitation of “two recitations,” without other modifiers, means at leasttwo recitations, or two or more recitations). Furthermore, in thoseinstances where a convention analogous to “at least one of A, B, and C,etc.” is used, in general such a construction is intended in the senseone having skill in the art would understand the convention (e.g., “asystem having at least one of A, B, and C” would include but not belimited to systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, and/or A, B, and Ctogether, etc.). In those instances where a convention analogous to “atleast one of A, B, or C, etc.” is used, in general such a constructionis intended in the sense one having skill in the art would understandthe convention (e.g., “a system having at least one of A, B, or C” wouldinclude but not be limited to systems that have A alone, B alone, Calone, A and B together, A and C together, B and C together, and/or A,B, and C together, etc.). It will be further understood by those withinthe art that virtually any disjunctive word and/or phrase presenting twoor more alternative terms, whether in the description, claims, ordrawings, should be understood to contemplate the possibilities ofincluding one of the terms, either of the terms, or both terms. Forexample, the phrase “A or B” will be understood to include thepossibilities of “A” or “B” or “A and B.”

In addition, where features or aspects of the disclosure are describedin terms of Markush groups, those skilled in the art will recognize thatthe disclosure is also thereby described in terms of any individualmember or subgroup of members of the Markush group.

As will be understood by one skilled in the art, for any and allpurposes, such as in terms of providing a written description, allranges disclosed herein also encompass any and all possible subrangesand combinations of subranges thereof. Any listed range can be easilyrecognized as sufficiently describing and enabling the same range beingbroken down into at least equal halves, thirds, quarters, fifths,tenths, etc. As a non-limiting example, each range discussed herein canbe readily broken down into a lower third, middle third and upper third,etc. As will also be understood by one skilled in the art all languagesuch as “up to,” “at least,” and the like include the number recited andrefer to ranges which can be subsequently broken down into subranges asdiscussed above. Finally, as will be understood by one skilled in theart, a range includes each individual member. Thus, for example, a grouphaving 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, agroup having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells,and so forth.

From the foregoing, it will be appreciated that various embodiments ofthe present disclosure have been described herein for purposes ofillustration, and that various modifications may be made withoutdeparting from the scope and spirit of the present disclosure.Accordingly, the various embodiments disclosed herein are not intendedto be limiting, with the true scope and spirit being indicated by thefollowing claims.

All references recited herein are incorporated herein by specificreference in their entirety.

1. A muscle assessment protocol comprising: attaching one or moresurface electromyometry (sEMG) sensors to skin of a subject so as to beoperably coupled with one or more muscles of the subject; operablycoupling the one or more sEMG sensors to a computing system; performingthe predetermined muscle activity of a muscle assessment protocol thatincludes one or more of a muscleprint protocol, stride rate tuningprotocol, controlled activity training protocol, or frequency-based, oramplitude-adjusted root mean square protocol; monitoring and/orrecording sEMG data of the one or more muscles during the predeterminedmuscle activity; and providing the sEMG data to the subject such thatthe subject can improve muscle performance for the predetermined muscleactivity by using the sEMG data.
 2. The muscle assessment protocol ofclaim 1, wherein the muscle activity includes static loading resistanceor dynamic muscle use.
 3. The muscle assessment protocol of claim 2,wherein the predetermined muscle activity is provided to the subject bythe computing system.
 4. The muscle assessment protocol of claim 3,wherein the muscle activity includes a continuous exercise routine, anoncontinuous exercise or routine.
 5. The muscle assessment protocol ofclaim 4, wherein the continuous exercise routine includes one or more ofwalking, jogging, running, sprinting, hiking, cycling, rollerblading,roller skating, skiing, cross-country skiing, rowing, swimming,snowboarding, yoga, pilates, or the like.
 6. The muscle assessmentprotocol of claim 4, wherein the noncontinuous exercise routine includesone or more of firing an arrow from a bow, weightlifting, golf swing,bat swing, ball throw, punch, kick, jumping, squatting, or the like. 7.The muscle assessment protocol of claim 4, wherein: in the muscleprintprotocol the one or more sensors each monitor muscle sEMG data of theone or more muscles while the subject performs the predeterminedactivity in order to determine the subject's muscular capabilities ofthe one or more muscles over a defined period of time or portionthereof; in the stride rate tuning protocol the one or more sensorsmonitor muscle sEMG data while the subject adjusts their caloricconsumption during a controlled activity based on sEMG data that ismeasured and/or analyzed, and the sEMG data is provided to the subjectin order to facilitate the adjustment of caloric consumption; in thecontrolled activity training protocol the subject maintainssubstantially a constant sEMG metric or metric derivative or metricintegral by varying muscle activity exertion during the predeterminedmuscle activity; or in the frequency-based, amplitude-adjusted root meansquare that includes displaying sEMG data that is adjusted to compensatefor muscle fatigue of the one or more muscles.
 8. The muscle assessmentprotocol of claim 4, wherein the sEMG data is a metric selected from:sEMG amplitude; instantaneous rectified sEMG amplitude; averagerectified sEMG amplitude; area under sEMG curve; area over sEMG curve;integrated sEMG; derivative sEMG; frequency-based, amplitude adjustedRMS sEMG; mean power frequency (MPF); muscle fatigue onset index (MFOI);or combination thereof.
 9. The muscle assessment protocol of claim 1,comprising: obtaining ECG data; and using the ECG data in conjunctionwith the sEMG data.
 10. A muscleprint protocol comprising: attaching oneor more surface electromyometry (sEMG) sensors to skin of a subject soas to be operably coupled with one or more muscles of the subject;operably coupling the one or more sEMG sensors to a computing system;performing the predetermined muscle activity of a muscleprint protocol,wherein in the muscleprint protocol the one or more sensors each monitormuscle sEMG data of the one or more muscles while the subject performsduring the predetermined activity in order to determine the subject'smuscular capabilities of the one or more muscles over a defined periodof time or portion thereof; monitoring and/or recording sEMG data of theone or more muscles during the predetermined muscle activity; andproviding the sEMG data to the subject such that the subject can improvemuscle performance for the predetermined muscle activity by using thesEMG data.
 11. The muscleprint protocol of claim 9, wherein themuscleprint protocol includes determining and/or generating a musclesEMG profile in response to the predetermined muscle activity over thedefined period of time or portion thereof.
 12. The muscleprint protocolof claim 11, wherein the muscleprint protocol includes a step-up testthat incrementally increases muscle output or muscle effort over one ormore step-up time periods of the predetermined muscle activity until thesubject is sufficiently fatigued or predetermined muscle activity timeperiod or predetermined repetitions of the muscle activity.
 13. Themuscleprint protocol of claim 12, comprising: graphing the muscleprintprotocol with sEMG data versus time; and providing the graph to thesubject.
 14. The muscleprint protocol of claim 13, comprising: accessingsEMG data of one or more other subjects from a database; and comparingthe subject's sEMG data with the sEMG data of the other subjects fromthe database.
 15. The muscleprint protocol of claim 14, comprising:filtering the one or more subjects from the database based on one ormore criteria; and providing sEMG data of the filtered one or moresubjects to the computing system; and generating a graph of thesubject's sEMG data with the sEMG data of the filtered one or moresubjects.
 16. The muscle assessment protocol of claim 10, comprising:obtaining ECG data; and using the ECG data in conjunction with the sEMGdata.
 17. A muscle improvement protocol comprising: attaching one ormore surface electromyometry (sEMG) sensors to skin of a subject so asto be operably coupled with one or more muscles of the subject; operablycoupling the one or more sEMG sensors to a computing system; performingthe predetermined muscle activity of a stride rate tuning protocol,wherein in the stride rate tuning protocol the one or more sensorsmonitor muscle sEMG data while the subject adjusts their caloricconsumption during a controlled activity based on sEMG data that ismeasured and/or analyzed, and the sEMG data is provided to the subjectin order to facilitate the adjustment of caloric consumption; monitoringand/or recording sEMG data of the one or more muscles during thepredetermined muscle activity; and providing the sEMG data to thesubject such that the subject can improve muscle performance for thepredetermined muscle activity by using the sEMG data.
 18. The muscleimprovement protocol of claim 17, comprising determining one or more ofa stride; stride rate; natural stride rate; haploid stride rate; stridedistance; or combination thereof.
 19. The muscle improvement protocol ofclaim 18, comprising determining cumulative energy cost for the one ormore muscles.
 20. The muscle improvement protocol of claim 19,comprising optimizing stride rate for the subject based on sEMG data soas to minimize energy consumption by the one or more muscles.
 21. Themuscle improvement protocol of claim 20, comprising: performing thepredetermined muscle activity at an initial constant rate or load for apredetermined time period or until exhaustion or until sEMG amplitudelevels; performing the predetermined muscle activity at a low constantrate or load that is lower than the initial constant rate or load; andincrementally increasing the rate or load of the predetermined muscleactivity at incremental time periods.
 22. The muscle improvementprotocol of claim 21, wherein the initial constant rate is substantiallythe subject's natural stride rate or estimate thereof.
 23. The muscleimprovement protocol of claim 22, comprising: computing energy costs ofdifferent stride rates; and providing the computed energy costs to thesubject.
 24. The muscle improvement protocol of claim 23, comprisingdetermining the subject's true natural stride rate.
 25. A muscleimprovement protocol comprising: attaching one or more surfaceelectromyometry (sEMG) sensors to skin of a subject so as to be operablycoupled with one or more muscles of the subject; operably coupling theone or more sEMG sensors to a computing system; performing thepredetermined muscle activity of a controlled activity trainingprotocol, wherein in the controlled activity training protocol thesubject maintains substantially a constant sEMG metric or metricderivative or metric integral by varying muscle activity exertion duringthe predetermined muscle activity; monitoring and/or recording sEMG dataof the one or more muscles during the predetermined muscle activity; andproviding the sEMG data to the subject such that the subject can improvemuscle performance for the predetermined muscle activity by using thesEMG data.
 26. The muscle improvement protocol of claim 25, comprising:analyzing the sEMG data; and determining a fatigue initiation time pointat which fatigue initiates after an initial time period.
 27. The muscleimprovement protocol of claim 26, comprising performing thepredetermined muscle activity again for a time period less than theinitial time period so that the subject ceases performance of thepredetermined muscle activity before the fatigue initiation time point.28. The muscle improvement protocol of claim 25, comprising controllinga second performance of the predetermined muscle activity based on sEMGdata collected during a first performance of the predetermined muscleactivity.
 29. The muscle improvement protocol of claim 25, comprisingholding substantially constant for control variables selected from sEMGamplitude, integrated sEMG, MPF, and MFOI; and varying performance ofthe predetermined muscle activity at the substantially constant controlvariable.
 30. The muscle improvement protocol of claim 29, performing adelayed fatigue onset training protocol.
 31. The muscle improvementprotocol of claim 25, comprising: performing a calibration protocol forthe predetermined muscle activity; determining an inflection point ofsEMG data during the calibration protocol, wherein the inflection pointidentifies an activity period from beginning the calibration protocol toa fatigue time point; and performing the predetermined muscle activityfor the activity period one or more times.
 32. The muscle improvementprotocol of claim 31, wherein prior to performance of the predeterminedmuscle activity after the calibration protocol includes the subjectwarming up with muscle groups other than involved in the predeterminedmuscle activity.
 33. The muscle improvement protocol of claim 32,wherein the activity period is performed at a maximum effort that can besubstantially sustained for the duration of the activity period.
 34. Themuscle improvement protocol of claim 33, comprising either resting orperforming a muscle activity different from the predetermined muscleactivity for a rest period between repetitions of the predeterminedmuscle activity.
 35. The muscle improvement protocol of claim 34,comprising maximizing caloric consumption during the activity period.36. The muscle improvement protocol of claim 31, comprising: measuringsEMG amplitude at inflection point; measuring final amplitude ofpredetermined muscle activity; calculating average sEMG amplitude forpost-inflection point data; performing the predetermined muscle activityanother time while holding the sEMG amplitude substantially constant.37. A muscle assessment protocol comprising: attaching one or moresurface electromyometry (sEMG) sensors to skin of a subject so as to beoperably coupled with one or more muscles of the subject; operablycoupling the one or more sEMG sensors to a computing system; performingthe predetermined muscle activity of an amplitude-adjusted root meansquare protocol, wherein in the frequency-based, amplitude-adjusted rootmean square that includes displaying sEMG data that is adjusted tocompensate for muscle fatigue of the one or more muscles; monitoringand/or recording sEMG data of the one or more muscles during thepredetermined muscle activity; and providing the sEMG data to thesubject such that the subject can improve muscle performance for thepredetermined muscle activity by using the sEMG data.
 38. The muscleassessment protocol of claim 37, comprising: providing an sEMG metric tothe subject during the predetermined muscle activity; and modulatingeffort by the subject during the predetermined muscle activity so as tomaintain the sEMG metric at substantially a constant.